Method and apparatus for reducing storage space of parameter table, device, and computer-readable storage medium

ABSTRACT

Embodiments of the present disclosure relate to a method and apparatus for reducing storage space of a parameter table. The method may include: storing the parameter table in a lookup table system configured to compute an output value of a non-linear function according to an input value of the non-linear function, the parameter table including only an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value; determining, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value, a parameter value corresponding to an index value associated with an input value on the other side; and computing the output value by using the input value on the other side and the determined corresponding parameter value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to Chinese Application No. 201910701383.8, filed on Jul. 31, 2019 and entitled “Method and Apparatus for Reducing Storage Space of Parameter Table, Device, and Computer-Readable Storage Medium,” the entire disclosure of which is hereby incorporated by reference.

TECHNICAL FIELD

Embodiments of the present disclosure generally relate to the field of text processing, and more specifically to a method and apparatus for reducing storage space of a parameter table, a device, and a computer-readable storage medium.

BACKGROUND

In recent years, deep learning has received widespread attention and has been applied to more and more scenarios. Many non-linear functions are used in the deep learning. The common non-linear functions include activation functions sigmoid, tanh, etc. The computation of these non-linear functions is often relatively complex, for example, complex operations such as exponential computation, logarithmic computation, and division are required. Therefore, if these complex operations are used directly for computation when implementing a related processor, there will be great challenges in many aspects such as area and power consumption of the processor and memories. To this end, an available method includes fitting these non-linear functions in a certain way, then saving the parameter table generated by the fitting, and computing these non-linear functions by calling the parameters stored in the parameter table using a lookup table (LUT) system when required.

However, when the lookup table system is used, a parameter table having a large storage space is required if high precision is to be achieved. At the same time, as the degree of computing parallelism of the non-linear functions increases, the number of parameter tables also needs to increase accordingly, which also brings a great challenge to the area of the processor. Furthermore, for the lookup table system in the related art, if no additional optimization scheme is adopted, when the storage space size of the parameter table is determined and certain precision is required, the range supported by the lookup table system may be relatively small. Although the input values beyond the parameter table may be optimized by certain means, a large loss of precision is inevitably caused.

SUMMARY

According to embodiments of the present disclosure, a compromise solution after the balance of resource area and flexibility is provided.

In a first aspect, an embodiment of the present disclosure provides a method for reducing storage space of a parameter table, the method including: storing the parameter table in a lookup table system, the lookup table system being configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table including an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value, and not including an index value associated with an input value on the other side of the median and a corresponding parameter value; determining, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value, a parameter value corresponding to the index value associated with the input value on the other side; and computing, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value.

In a second aspect, an embodiment of the present disclosure provides an apparatus for reducing storage space of a parameter table, the apparatus including: a storage module, configured to store the parameter table in a lookup table system, the lookup table system being configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table including an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value, and not including an index value associated with an input value on the other side of the median and a corresponding parameter value; a first determining module, configured to determine, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value, a parameter value corresponding to the index value associated with the input value on the other side; and a first computing module, configured to compute, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value.

In a third aspect, an embodiment of the present disclosure provides an electronic device. The electronic device includes: one or more processors; and a storage apparatus, for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method according to the first aspect.

In a fourth aspect, an embodiment of the present disclosure provides a computer readable storage medium, storing a computer program thereon, where the computer program, when executed by a processor, implements the method according to the first aspect.

It should be appreciated that the description of the Summary is not intended to limit the key or important features of embodiments of the present disclosure, or to limit the scope of the present disclosure. Other features of the present disclosure will become readily comprehensible through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent with reference to the accompanying drawings and detailed descriptions below. The same or similar reference numerals in the drawings denote the same or similar elements.

FIG. 1 shows a schematic diagram of a lookup table system 100 according to some embodiments of the present disclosure;

FIG. 2 shows a flowchart of a method 200 for reducing storage space of a parameter table according to some embodiments of the present disclosure;

FIG. 3 shows a schematic diagram 300 of processing for piecewise fitting according to some embodiments of the present disclosure;

FIG. 4 shows a schematic diagram 400 of processing for piecewise fitting according to some other embodiments of the present disclosure;

FIG. 5 shows a schematic diagram 500 of processing for interpolation fitting according to some embodiments of the present disclosure;

FIG. 6 shows a schematic diagram 600 of processing for interpolation fitting according to some other embodiments of the present disclosure;

FIG. 7 shows a schematic block diagram of an apparatus 700 for reducing storage space of a parameter table according to some embodiments of the present disclosure; and

FIG. 8 shows a block diagram of a computing device 800 capable of implementing some embodiments of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be appreciated that the present disclosure may be implemented in various forms and should not be construed as limited to embodiments described here, and these embodiments are provided in turn for more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are merely illustrative, but are not intended to limit the scope of the present disclosure.

In the description of embodiments of the present disclosure, the term “include” and the like should be interpreted as open inclusion, i.e., “include but not limited to”. The term “based on” should be interpreted as “at least partially based on”. The term “some embodiments” or “embodiments” should be interpreted as “at least some embodiments”. The terms “first”, “second” and the like may indicate different or identical objects. Other explicit and implicit definitions may also be included below.

As mentioned above, non-linear functions are frequently used in deep learning algorithms, for example, in steps such as activation functions and layers for classification. If these non-linear functions are directly computed, complex operations such as exponential operation, logarithmic operation, erf error function, and division operation are required, which may cause a large area overhead of a processor. Therefore, the non-linear functions can be computed by means of a lookup table system. However, when the lookup table system is used, a too small parameter table cannot be used in order to avoid excessive loss of precision in the lookup table. For example, the parameter table may be configured at 2K×32 bits. On the other hand, in order to achieve a high computing throughput of the processor, a relatively high degree of computing parallelism needs to be adopted. However, the degree of parallelism of the parameter table needs to be kept consistent with that of the processor. For example, if the desired degree of computing parallelism is P, then the required total capacity of the parameter table is (2×P)×K×32 bits, so the final memory area required by the parameter table also brings a challenge.

In view of the above problems, some embodiments of the present disclosure propose a compromise solution after the balance of resource area and flexibility, where the increase in selection of several lookup table modes can not only save half the storage area, but also can flexibly support non-linear functions of multiple characteristics to a certain extent, and the computation precision is substantially not affected; and this solution does not need additional computing resources. Specifically, most of the non-linear functions used in deep learning have certain symmetric forms. For example, common tanh, sigmoid, and erf functions are centrosymmetric functions, and some other functions are axisymmetric (mirror-symmetric) functions. Therefore, the storage space of the parameter table can be reduced by reasonably using the symmetry of these common functions, and the parameter table occupying the reduced storage space achieves the same or similar supportable data range, or the data range supportable by the parameter table is expanded without increasing the storage space of the parameter table. According to some embodiments of the present disclosure, the lookup table system may support at least three modes of configuration, respectively: a centrosymmetric mode, an axisymmetric mode, and a normal mode.

Some embodiments of the present disclosure will be described below with reference to the accompanying drawings.

FIG. 1 shows a schematic diagram of a lookup table system 100 according to some embodiments of the present disclosure. It should be understood that the structure and function of the lookup table system 100 are described for exemplary purpose only, but do not imply any limitation on the scope of the present disclosure. Some embodiments of the present disclosure may also be applied to lookup table systems having different structures and/or functions.

As shown in FIG. 1, the lookup table system 100 includes a storage apparatus 110 and a processing module 120. The storage apparatus 110 is configured to store a parameter table for computing a non-linear function and various data required for the operation of the lookup table system 100. The processing module 120 is configured to perform various operations required for computing non-linear functions by using the lookup table system 100. More specifically, the processing module 120 includes a processing logic 121 and a mode control module 122. The processing logic 121 is configured to specifically compute the non-linear functions having various symmetric forms, and the mode control module 122 is configured to control in which symmetric mode the processing logic 121 should operate.

As mentioned above, the lookup table system 100 may be configured to store a parameter table and compute non-linear functions. In order to achieve parallel computation, the lookup table system 100 may store a plurality of parameter tables and have a plurality of processing modules 120, that is, the number of parameter tables stored by the lookup table system 100 equals to the number of corresponding processing modules 120 of the lookup table system 100, and equals to the number of parallel computations for the non-linear functions. Generally, a lookup table system 100 may have only one read-write port. When parallel reading is performed, indexes read by different channels are different, but each channel of reading needs to occupy a read port. Generally, at least one independent parameter table is required for each non-linear function, and the number of parameter tables may depend on the number of parameters involved. A fixed lookup table system 100 may be constructed. When computing a non-linear function, the parameter table in the lookup table system is configured as parameters for this function, or the parameter table for this function is stored in the lookup table system 100. When computing another non-linear function, only the parameters in the parameter table are replaced or the parameter table for this function is stored. The values in the parameter table are preset according to the non-linear function to be computed. When the lookup table system 100 operates, after the computation of one non-linear function is completed, another non-linear function may be computed by replacing the parameters in the parameter table or storing a parameter table for this function. The lookup table system 100 may also implement parallel computation between different non-linear functions as required. At this time, a plurality of parameter tables need to be configured or stored in the lookup table system 100.

Hereinafter, the operating principle of the lookup table system 100 shown in FIG. 1 will be described in detail with reference to the accompanying drawings.

FIG. 2 shows a flowchart of a method 200 for reducing storage space of a parameter table according to some embodiments of the present disclosure. For example, the method 200 may be performed by the lookup table system 100 shown in FIG. 1. Each operation of the method 200 will be described in detail below with reference to FIG. 3 to FIG. 6. It should be understood that the method 200 may also include additional operations not shown and/or omit the operations shown. The scope of the present disclosure is not limited in this respect.

In block 210, the lookup table system 100 stores a parameter table. According to an embodiment of the present disclosure, the parameter table is stored in the storage apparatus 110. The parameter table is obtained by fitting a non-linear function, and has been computed and configured before being stored in the storage apparatus 110 for subsequent computation, so that when computing the non-linear function, only the parameter table needs to be read from the storage apparatus 110. As mentioned above, each non-linear function corresponds to at least one parameter table. According to embodiments of the present disclosure, the step of block 210 may be performed by the processing module 120. Two fitting methods are used in embodiments of the present disclosure, that is, a piecewise fitting method and an interpolation fitting method.

In the piecewise fitting method, a non-linear function is divided into a plurality of segments, and each segment is fitted into the form of y=k*x+b, where k is the slope and b is the intercept on the y axis, that is, each segment is regarded as a linear function. At this time, two parameter tables are required, respectively a k parameter table for storing parameters k and a b parameter table for storing parameters b. When the lookup table system 100 computes a non-linear function, the input value of the non-linear function is first converted into an index of parameter tables through a simple linear transformation, then two corresponding parameters k and b are read from the parameter table k and the parameter table b through the index associated with the input value, and an output value of the non-linear function is finally computed by computing k*x+b.

According to embodiments of the present disclosure, the linear transformation is performed on the input value of the non-linear function. For example, the input value x may be any value, but the index of parameter tables may range from 0 to 511 (the length of the lookup table is 512). At this time, the input value x needs to be transformed to an integer value between 0 and 511. For example, if the value of a parameter table supported by the input value x is 10 to 12, a floating-point number in 10 to 12 needs to be transformed into an integer index between 0 and 511. This process is a linear transformation for the input value.

In the interpolation fitting method, y values of a plurality of sampling points are stored in a parameter table, the values of two or more points adjacent to the input value are read from the parameter table when computing a non-linear function, and the interpolation computation is performed. For example, the input value is x, the indexes adjacent to two sides of the input value x in the parameter table of the input value are respectively an index associated with x1 on one side of the input value x and its corresponding parameter y1, and an index associated with x2 on the other side of the input value x and its corresponding parameter y2. At this time, the output value is computed by computing y=(alpha*y1+(1−alpha)*y2), where alpha represents the ratio (x2−x)/(x2−x1), that is, the ratio of the distance between the input x and the x2 on the x axis relative to the (x2, y2) sampling point to the distance between x1 and x2.

For the above two fitting methods used in some embodiments of the present disclosure, the error is smaller if the sampling points are denser. The minimum value of sampling points on the x axis is set to min, and the maximum value on the x axis is set to max. The step of linearly transforming the index associated with the input value x may be written as index=(x−min)*num_table_entry/(max−min), where num_table_entry represents the number of parameters stored in the parameter table. If the input range of the input value x falls between min and max, the error may be within a controllable range. If the input value x falls beyond this range, the error may become larger. Therefore, in the related art, after the size of a parameter table in the storage space is determined, a balance compromise between the precision and the supportable data range is also required. That is, when the supportable data range becomes large, it often means that the sampling density becomes small and the precision decreases. When the supportable data range is small, it often means that the sampling density is large and the precision is high. The technical solutions described in some embodiments of the present disclosure can also obviously solve this problem in the related art.

Returning to block 210, according to some embodiments of the present disclosure, the parameter table stored in the storage apparatus 110 is configured to compute the output value of the non-linear function based on the input value of the non-linear function. As mentioned above, the lookup table system 100 according to some embodiments of the present disclosure may support a centrosymmetric mode, an axisymmetric mode, and a normal mode. The normal mode is mainly for a non-symmetric non-linear function, only the min and max values for the range of the lookup table are configured using the conventional lookup table method, and details are not described herein again. For the centrosymmetric mode and the axisymmetric mode, only the min and max values for the positive or negative half range of the input values need to be configured, and only the parameters corresponding to the positive or negative half range of the input values need to be stored in the parameter table. If the input value is actually negative, the read parameter value or the finally computed output value is negated, and the specific operation may be different dependent on the fitting method used by the lookup table system 100. Therefore, according to some embodiments of the present disclosure, for block 210, the parameter table includes an index value associated with an input value on one side of a median in a domain of a non-linear function and a parameter value corresponding to the index value, and does not include an index value associated with the input value on the other side of the median and a corresponding parameter value. The median may be construed as the center of the non-linear function domain, that is, an input value of 0.

In block 220, the lookup table system 100 determines, by using the corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value, a parameter value corresponding to the index value associated with the input value on the other side. According to some embodiments of the present disclosure, because only half of indexes and parameter values are stored in the parameter table, when an input value is not associated with the stored index (e.g., the input value is negative), the stored index value needs to be found in the parameter table through the input value, and then the corresponding parameter value is found for computation. According to some embodiments of the present disclosure, block 220 may specifically include the following steps: negating the input value on the other side; and determining the corresponding parameter value by using the index value associated with the negated input value on the other side and the corresponding relationship. According to embodiments of the present disclosure, the step of block 220 may be performed by the processing module 120.

In block 230, the lookup table system 100 computes, based on the symmetric form of the non-linear function and the computation formula associated with the non-linear function, an output value by using the input value on the other side and the determined corresponding parameter value. According to some embodiments of the present disclosure, the computation of the non-linear function may be different for different symmetric form (e.g., centrosymmetric or axisymmetric). In addition, since the non-linear function is fitted, the output value of the non-linear function needs to be computed by the fitted function (i.e., the computation formula). According to some embodiments of the present disclosure, the step of block 230 may be performed by the processing module 120.

For the foregoing two fitting methods, that is, piecewise fitting and interpolation fitting, the specific content of the method 200 may be simply described as follows: when the piecewise fitting y=k*x+b is used, the two parameter values k and b are stored in the parameter table. If the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, |x| is used when generating the index of the parameter table by means of linear transformation of the input value, and if the input value x is more than or equal to 0, the output value y is finally computed as y=k*x+b, otherwise, the output value y is finally computed as y=k*x−b. If the mode control module 122 configures the processing logic 121 to an axisymmetric mode, |x| is used when generating the index of the parameter table by means of linear transformation of the input value, and if the input value x is more than or equal to 0, the output value y is finally computed as y=k*x+b, otherwise, the output value y is finally computed as y−k*x+b. According to some embodiments of the present disclosure, the lookup table system 100 of the present disclosure may also support the processing in the normal mode, no special processing is required at this time, and the output value is y=k*x+b regardless of the input value x. Correspondingly, when the interpolation fitting method is used, if the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, |x| is used when generating the index of the parameter table by means of linear transformation of the input value, and if the input value x is negative, the computed negative output value y′ needs to be negated to obtain a final output value y. If the mode control module 122 configures the processing logic 121 to a mirror-symmetric mode, |x| is used when generating the index of the parameter table by means of linear transformation of the input value, and no additional processing is required for the output value y. In the normal mode, no special processing is required, and the input value x and the output value y are both original values.

It should be noted that, in addition to the above two non-linear function fitting methods, some embodiments of the present disclosure are also applicable to lookup table systems using other fitting methods.

Other embodiments of the method 200 are further described below with reference to FIG. 3 to FIG. 6.

FIG. 3 shows a schematic diagram 300 of processing for piecewise fitting according to some embodiments of the present disclosure. With reference to the scenario shown in FIG. 3, block 230 of the method 200 may be refined as negating the parameter value among the determined corresponding parameter values except the parameter value associated with the constant term in the computation formula; and computing the output value based on the computation formula by using the input value on the other side, the parameter value associated with the constant term in the computation formula, and the negated parameter value. In the schematic diagram 300, 301 is an input value x of a non-linear function, 313 is an output value y of the non-linear function, 302, 307 and 309 are negating modules, 303, 308 and 310 are multiplexers (MUX), 304 is a linear transformation module, 305 is a k parameter table, 306 is a b parameter table, 311 is a multiplier, 312 is an adder, and 314 is a multiplexer control module for controlling the output values of the multiplexers 303, 308 and 310.

In the schematic diagram 300, the non-linear function is fitted to the form of y=k*x+b. Accordingly, the input value 301 is inputted to the multiplexer 303 and the multiplier 311, and is further inputted to the multiplexer 303 through the negating module 302. The multiplexer control module 314 controls the multiplexer 303 to input the input value 301 or the negated input value 301 to the linear transformation module 304, and the linear transformation module 304 performs a linear transformation on the input value 301 or the negated input value 301, and inputs the obtained index value into the k parameter table 305 and the b parameter table 306. The parameter k obtained by the k parameter table 305 through the index value is inputted to the multiplexer 308, and is further inputted to the multiplexer 308 through the negating module 307. The multiplexer control module 314 controls the multiplexer 308 to input the parameter k or the negated parameter k to the multiplier 311. The multiplier 311 multiplies the input value 301 and the parameter k or the negated parameter k and inputs the product to the adder 312. The parameter b obtained by the b parameter table 306 through the index value is inputted to the multiplexer 310, and is further inputted to the multiplexer 310 through the negating module 309. The multiplexer control module 314 controls the multiplexer 310 to input the parameter b or the negated parameter b to the adder 312. The adder 312 adds the product inputted by the multiplier 311 and the parameter b or the negated parameter b inputted by the multiplexer 310, and outputs the addition result as an output value 313.

In the scenario shown in the schematic diagram 300, the multiplexer control module 314 controls the output values of the multiplexers 303, 308 and 310 according to the symmetric mode controlled by the mode control module 122. Specifically, if the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, the multiplexer control module 314 controls the multiplexer 303 to output a negated input value 301 when the input value 301 is negative, and output the input value 301 when the input value 301 is not negative; controls the multiplexer 308 to output the parameter k; and controls the multiplexer 310 to output the negated parameter b when the input value 301 is negative, and output the parameter b when the input value 301 is not negative. If the mode control module 122 configures the processing logic 121 to an axisymmetric mode, the multiplexer control module 314 controls the multiplexer 303 to output a negated input value 301 when the input value 301 is negative, and output the input value 301 when the input value 301 is not negative; controls the multiplexer 308 to output a negated parameter k when the input value 301 is negative, otherwise, and output the parameter k when the input value 301 is not negative; and controls the multiplexer 310 to output the parameter b.

With the configuration shown in the schematic diagram 300, the method 200 can be implemented.

FIG. 4 shows a schematic diagram 400 of processing for piecewise fitting according to some other embodiments of the present disclosure. With reference to the scenario shown in FIG. 4, block 230 of the method 200 may be refined as computing the output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value. In the schematic diagram 400, 401 is an input value x of a non-linear function, 411 is an output value y of the non-linear function, 402 and 409 are negating modules, 403 and 410 are multiplexers (MUX), 404 is a linear transformation module, 405 is a k parameter table, 406 is a b parameter table, 407 is a multiplier, 408 is an adder, and 412 is a multiplexer control module for controlling the output values of the multiplexers 403 and 410.

In the schematic diagram 400, the non-linear function is also fitted into the form of y=k*x+b. The operation of each component is similar to that described above with respect to the schematic diagram 300, and details are not described herein again.

In the scenario shown in the schematic diagram 400, the multiplexer control module 314 controls the output values of the multiplexers 403 and 410 according to the symmetric mode controlled by the mode control module 122. Specifically, if the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, the multiplexer control module 412 controls the multiplexer 403 to output a negated input value 401 when the input value 401 is negative, and output the input value 401 when the input value 401 is not negative; and controls the multiplexer 410 to output a negated addition result when the input value 401 is negative, and output the addition result when the input value 401 is not negative. If the mode control module 122 configures the processing logic 121 to an axisymmetric mode, the multiplexer control module 412 controls the multiplexer 403 to output a negated input value 401 when the input value 401 is negative, and output the input value 401 when the input value 401 is not negative; and controls the multiplexer 410 to output the addition result.

With the configuration shown in the schematic diagram 400, the method 200 can be implemented.

FIG. 5 shows a schematic diagram 500 of processing for interpolation fitting according to some embodiments of the present disclosure. With reference to the scenario shown in FIG. 5, block 230 of the method 200 may be refined as negating the input value on the other side; computing a negative output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value; and computing an output value by negating the negative output value. In the schematic diagram 500, 501 is an input value x of a non-linear function, 514 is an output value y of the non-linear function, 502 and 512 are negating modules, 503 and 513 are multiplexers (MUX), 504 is a linear transformation module, 505 and 506 are an x1 index and an x2 index outputted by the linear transformation module for x1 and x2, 507 is a y parameter table, 508 and 509 are y1 and y2 outputted by the y parameter table 507 based on the x1 index 505 and the x2 index 506, 510 is alpha and 1-alpha outputted by the linear transformation module 504 for x1 and x2, 511 is an interpolation computing module, and 415 is a multiplexer control module for controlling the output values of the multiplexers 503 and 513.

In the schematic diagram 500, the non-linear function is fitted into the form of y=(alpha*y1+(1−alpha)*y2). Accordingly, the input value 501 is inputted to the multiplexer 503, and is further inputted to the multiplexer 503 through the negating module 502. The multiplexer control module 515 controls the multiplexer 503 to input the input value 501 or the negated input value 501 to the linear transformation module 504, the linear transformation module 504 performs a linear transformation on the input value 501 or the negated input value 501, inputs the x1 index 505 and the x2 index 506 obtained for x1 and x2 on two sides of the input value x to the y parameter table 507, and inputs the alpha and the 1-alpha obtained for x1 and x2 to the interpolation computing module 511. The y parameter table 507 inputs the y1 508 and the y2 509 obtained based on the x1 index 505 and the x2 index 506 to the interpolation computing module 511. The interpolation computing module 511 computes an output value or a negative output value based on the y1 508, the y2 509, the alpha, and the 1-alpha, and inputs the output value or the negative output value to the multiplexer 513 directly or through the negating module 512. The multiplexer control module 515 controls the multiplexer 513 to output “the output value or the negative output value” or “the negated output value or the negative output value” as the output value 513.

In the scenario shown in the schematic diagram 500, the multiplexer control module 515 controls the output values of the multiplexers 503 and 513 according to the symmetric mode controlled by the mode control module 122. Specifically, if the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, the multiplexer control module 515 controls the multiplexer 503 to output a negated input value 501 when the input value 501 is negative, and output the input value 501 when the input value 501 is not negative; and controls the multiplexer 513 to output “the negated output value or the negative output value” when the input value 501 is negative, and output “the output value or the negative output value” when the input value 501 is negative. If the mode control module 122 configures the processing logic 121 to an axisymmetric mode, the multiplexer control module 515 controls the multiplexer 503 to output a negated input value 501 when the input value 501 is negative, and output the input value 501 when the input value 501 is negative; and controls the multiplexer 513 to output “the output value or the negative output value”.

With the configuration shown in the schematic diagram 500, the method 200 can be implemented.

FIG. 6 shows a schematic diagram 600 of processing for interpolation fitting according to some other embodiments of the present disclosure. With reference to the scenario shown in FIG. 6, block 230 of the method 200 may be refined as negating the input value on the other side; negating the determined corresponding parameter value; and computing the output value based on the computation formula by using the negated input value on the other side and the negated determined corresponding parameter value. In the schematic diagram 600, 601 is an input value x of a non-linear function, 616 is an output value y of the non-linear function, 602, 611 and 613 are negating modules, 603, 612 and 614 are multiplexers (MUX), 604 is a linear transformation module, 605 and 606 are an x1 index and an x2 index outputted by the linear transformation module for x1 and x2, 608 is a y parameter table, 609 and 610 are y1 and y2 outputted by the y parameter table 608 based on the x1 index 605 and the x2 index 606, 607 is alpha and 1-alpha outputted by the linear transformation module 604 for x1 and x2, 615 is an interpolation computing module, and 617 is a multiplexer control module for controlling the output values of the multiplexers 603, 612 and 614.

In the schematic diagram 600, the non-linear function is also fitted into the form of y=(alpha*y1+(1−alpha)*y2). The operation of each component is similar to that described above with respect to the schematic diagram 500, and details are not described herein again.

In the scenario shown in the schematic diagram 600, the multiplexer control module 617 controls the output values of the multiplexers 603, 612 and 614 according to the symmetric mode controlled by the mode control module 122. Specifically, if the mode control module 122 configures the processing logic 121 to a centrosymmetric mode, the multiplexer control module 617 controls the multiplexer 603 to output a negated input value 601 when the input value 601 is negative, and output the input value 601 when the input value 601 is not negative; and controls the multiplexers 612 and 614 to output negated y1 and negated y2 respectively when the input value 601 is negative, and output y1 and y2 respectively when the input value 601 is not negative. If the mode control module 122 configures the processing logic 121 to an axisymmetric mode, the multiplexer control module 617 controls the multiplexer 603 to output a negated input value 601 when the input value 601 is negative, and output the input value 601 when the input value 601 is not negative; and controls the multiplexers 612 and 614 to output y1 and y2 respectively.

With the configuration shown in the schematic diagram 600, the method 200 can be implemented.

Compared with the conventional solution, the technical solution of the present disclosure can reduce the parameter table storage space for the non-linear function in the lookup table system. Thus, the lookup table of the same size can cover the larger input value range of the non-linear function, so that higher precision of the lookup table can be achieved. In addition, the technical solution of the present disclosure is suitable for various fitting methods of the lookup table system, and hardly adds the computing requirements.

Some embodiments of the present disclosure further provide a corresponding apparatus for implementing the above method or process. FIG. 7 shows a schematic block diagram of an apparatus 700 for reducing storage space of a parameter table according to some embodiments of the present disclosure. The apparatus 700 may be implemented in, for example, the lookup table system 100 of FIG. 1. As shown in FIG. 7, the apparatus 700 may include a storage module 710, a first determining module 720, and a first computing module 730.

In some embodiments, the storage module 710 may be configured to store the parameter table in a lookup table system, where the lookup table system is configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table includes an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value, and does not include an index value associated with an input value on the other side of the median and a corresponding parameter value. The operation of the storage module 710 is similar to that described with reference to block 210 of FIG. 2, and details are not repeated herein again.

In some embodiments, the first determining module 720 may be configured to determine, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value, a parameter value corresponding to the index value associated with the input value on the other side. The operation of the first determining module 720 is similar to that described with reference to block 220 of FIG. 2, and details are not repeated herein again.

According to some embodiments of the present disclosure, the first determining module 720 may include (not shown): a first negating module, configured to negate the input value on the other side; and a second determining module, configured to determine the corresponding parameter value by using the index value associated with the negated input value on the other side and the corresponding relationship. The operations of the first negating module and the second determining module are similar to the operations described with reference to block 220 of FIG. 2, and details are not repeated herein again.

In some embodiments, the first computing module 730 may be configured to compute, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value. The operation of the first computing module 730 is similar to that described with reference to block 230 of FIG. 2, and details are not repeated herein again.

According to some embodiments of the present disclosure, the first computing module 730 may include (not shown): a second negating module, configured to negate the parameter value among determined corresponding parameter values except the parameter value associated with a constant term in the computation formula; and a second computing module, configured to compute the output value based on the computation formula by using the input value on the other side, the parameter value associated with the constant term in the computation formula, and the negated parameter value. The operations of the second negating module and the second computing module are similar to the operations described with reference to block 230 of FIG. 2, and details are not repeated herein again.

According to some embodiments of the present disclosure, the first computing module 730 may include (not shown): a third computing module, configured to compute the output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value. The operation of the third computing module is similar to that described with reference to block 230 of FIG. 2, and details are not repeated herein again.

According to some embodiments of the present disclosure, the first computing module 730 may include (not shown): a first negating module, configured to negate the input value on the other side; a fourth computing module, configured to compute a negative output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value; and a fifth computing module, configured to compute the output value by negating the negative output value. The operations of the first negating module, the fourth computing module, and the fifth computing module are similar to the operations described with reference to block 230 of FIG. 2, and details are not repeated herein again.

According to some embodiments of the present disclosure, the first computing module 730 may include (not shown): a first negating module, configured to negate the input value on the other side; a third negating module, configured to negate the determined corresponding parameter value; and a sixth computing module, configured to compute the output value based on the computation formula by using the negated input value on the other side and the negated determined corresponding parameter value. The operations of the first negating module, the third negating module, and the sixth computing module are similar to the operations described with reference to block 230 of FIG. 2, and details are not repeated herein again.

It should be understood that the modules described in the apparatus 700 may correspond to the respective steps in the method 200 described with reference to FIG. 2. In addition, the operations and features of the modules included in the apparatus 700 may correspond to the operations and features described with reference to FIG. 2 to FIG. 6 and have the same effects, and the specific details are not described again.

The modules included in the apparatus 700 may be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more modules may be implemented using software and/or firmware, for example, machine-executable instructions stored on a storage medium. In addition to or instead of the machine-executable instructions, some or all of the modules in the apparatus 700 may be implemented at least partially by one or more hardware logic components. As an example instead of limitations, example types of hardware logic components that may be used include: a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), a system on chip (SOC), a complex programmable logic device (CPLD), etc.

These modules shown in FIG. 7 may be partially or entirely implemented as hardware modules, software modules, firmware modules, or any combination thereof. Particularly, in some embodiments, the flows, methods or processes described above may be implemented by a storage system or a host corresponding to the storage system or hardware in other computing device independent of the storage system.

FIG. 8 shows a schematic block diagram of an example computing device 800 that can be configured to implement some embodiments of the present disclosure. The device 800 may be configured to implement the lookup table system 100 of FIG. 1. As shown in FIG. 8, the device 800 includes a central processing unit (CPU) 801, which may execute various appropriate operations and processes based on computer program instructions stored in a read-only memory (ROM) 802 or computer program instructions loaded from a storage unit 808 to a random access memory (RAM) 803. The RAM 803 may also store various programs and data required by the operations of the device 800. The CPU 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.

A plurality of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, e.g., a keyboard, a mouse, etc.; an output unit 807, e.g., various types of displays, speakers, etc.; a storage unit 808, e.g., a magnetic disk, an optical disk, etc.; and a communication unit 809, e.g., a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.

The processing unit 801 executes the various methods and processes described above, such as the method 200. For example, in some embodiments, the method 200 may be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 808. In some embodiments, some or all of the computer program may be loaded and/or installed to the device 800 via the ROM 802 and/or the communication unit 809. When the computer program is loaded to the RAM 803 and executed by the CPU 801, one or more steps of the method 200 described above may be executed. Alternatively, in other embodiments, the CPU 801 may be configured to execute the method 200 by any other suitable means (for example, by means of firmware).

Program codes for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer or other programmable data processing apparatus such that the program codes, when executed by the processor or controller, enables the functions/operations specified in the flowcharts and/or block diagrams being implemented. The program codes may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on the remote machine, or entirely on the remote machine or server.

In the context of the present disclosure, the machine readable medium may be a tangible medium that may contain or store programs for use by or in connection with an instruction execution system, apparatus, or device. The machine readable medium may be a machine readable signal medium or a machine readable storage medium. The machine readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine readable storage medium may include an electrical connection based on one or more wires, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.

In addition, although various operations are described in a specific order, this should not be understood that such operations are required to be performed in the specific order shown or in sequential order, or all illustrated operations should be performed to achieve the desired result. Multitasking and parallel processing may be advantageous in certain circumstances. Likewise, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented in a plurality of implementations, either individually or in any suitable sub-combination.

Although embodiments of the present disclosure are described in language specific to structural features and/or method logic actions, it should be understood that the subject matter defined in the appended claims is not limited to the specific features or actions described above. Instead, the specific features and actions described above are merely exemplary forms of implementing the claims. 

What is claimed is:
 1. A method for reducing storage space of a parameter table, comprising: storing the parameter table in a lookup table system, the lookup table system being configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table comprising an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value associated with the input value on one side of the median, and not comprising an index value associated with an input value on the other side of the median and a corresponding parameter value, the corresponding parameter value being a parameter value corresponding to the index value associated with the input value on the other side of the median; determining, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value associated with the input value on one side of the median, the parameter value corresponding to the index value associated with the input value on the other side; and computing, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value.
 2. The method according to claim 1, wherein the determining the parameter value corresponding to the index value associated with the input value on the other side comprises: negating the input value on the other side; and determining the corresponding parameter value by using the index value associated with the negated input value on the other side and the corresponding relationship.
 3. The method according to claim 2, wherein the computing the output value comprises: computing the output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value.
 4. The method according to claim 2, wherein the computing the output value comprises: negating the parameter value among determined corresponding parameter values except the parameter value associated with a constant term in the computation formula; and computing the output value based on the computation formula by using the input value on the other side, the parameter value associated with the constant term in the computation formula, and the negated parameter value.
 5. The method according to claim 2, wherein the computing the output value comprises: negating the input value on the other side; computing a negative output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value; and computing the output value by negating the negative output value.
 6. The method according to claim 2, wherein the computing the output value comprises: negating the input value on the other side; negating the determined corresponding parameter value; and computing the output value based on the computation formula by using the negated input value on the other side and the negated determined corresponding parameter value.
 7. An apparatus for reducing storage space of a parameter table, comprising: at least one processor; and a memory storing instructions, the instructions when executed by the at least one processor, causing the at least one processor to perform operations, the operations comprising: storing the parameter table in a lookup table system, the lookup table system being configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table comprising an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value associated with the input value on one side of the median, and not comprising an index value associated with an input value on the other side of the median and a corresponding parameter value, the corresponding parameter value being a parameter value corresponding to the index value associated with the input value on the other side of the median; determining, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value associated with the input value on one side of the median, the parameter value corresponding to the index value associated with the input value on the other side; and computing, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value.
 8. The apparatus according to claim 7, wherein the determining the parameter value corresponding to the index value associated with the input value on the other side comprises: negating the input value on the other side; and determining the corresponding parameter value by using the index value associated with the negated input value on the other side and the corresponding relationship.
 9. The apparatus according to claim 8, wherein the computing the output value comprises: computing the output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value.
 10. The apparatus according to claim 8, wherein the computing the output value comprises: negating the parameter value among determined corresponding parameter values except the parameter value associated with a constant term in the computation formula; and computing the output value based on the computation formula by using the input value on the other side, the parameter value associated with the constant term in the computation formula, and the negated parameter value.
 11. The apparatus according to claim 8, wherein the computing the output value comprises: negating the input value on the other side; computing a negative output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value; and computing the output value by negating the negative output value.
 12. The apparatus according to claim 8, wherein the computing the output value comprises: negating the input value on the other side; negating the determined corresponding parameter value; and computing the output value based on the computation formula by using the negated input value on the other side and the negated determined corresponding parameter value.
 13. A non-transitory computer-readable storage medium, storing a computer program thereon, wherein the computer program, when executed by a processor, causes the processor to perform operations, the operations comprising: storing a parameter table in a lookup table system, the lookup table system being configured to compute an output value of a non-linear function according to an input value of the non-linear function, and the parameter table comprising an index value associated with an input value on one side of a median in a domain of the non-linear function and a parameter value corresponding to the index value associated with the input value on one side of the median, and not comprising an index value associated with an input value on the other side of the median and a corresponding parameter value, the corresponding parameter value being a parameter value corresponding to the index value associated with the input value on the other side of the median; determining, by using a corresponding relationship between the index value associated with the input value on one side and the parameter value corresponding to the index value associated with the input value on one side of the median, the parameter value corresponding to the index value associated with the input value on the other side; and computing, based on a symmetric form of the non-linear function and a computation formula associated with the non-linear function, the output value by using the input value on the other side and the determined corresponding parameter value.
 14. The non-transitory computer-readable storage medium according to claim 13, wherein the determining the parameter value corresponding to the index value associated with the input value on the other side comprises: negating the input value on the other side; and determining the corresponding parameter value by using the index value associated with the negated input value on the other side and the corresponding relationship.
 15. The non-transitory computer-readable storage medium according to claim 14, wherein the computing the output value comprises: computing the output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value.
 16. The non-transitory computer-readable storage medium according to claim 14, wherein the computing the output value comprises: negating the parameter value among determined corresponding parameter values except the parameter value associated with a constant term in the computation formula; and computing the output value based on the computation formula by using the input value on the other side, the parameter value associated with the constant term in the computation formula, and the negated parameter value.
 17. The non-transitory computer-readable storage medium according to claim 14, wherein the computing the output value comprises: negating the input value on the other side; computing a negative output value based on the computation formula by using the negated input value on the other side and the determined corresponding parameter value; and computing the output value by negating the negative output value.
 18. The non-transitory computer-readable storage medium according to claim 14, wherein the computing the output value comprises: negating the input value on the other side; negating the determined corresponding parameter value; and computing the output value based on the computation formula by using the negated input value on the other side and the negated determined corresponding parameter value. 